Grid computing is a technology for dynamically sharing geographically and organizationally distributed various types of CPUs, memories, information, and other resources according to the user's demand and provider's policy so that those resources work together to process problems. One of the functions required for such grid computing is a function for collecting and delivering information on resources such as CPU, operating systems (OS), and memories used in grid computing.
An example of a conventional resource information collection and delivery system is described in Non-Patent Document 1 and Non-Patent Document 2.
As shown in FIG. 24, this conventional resource information collection and delivery system comprises a resource use device 300 that has filter expression sending means 301, a resource providing device 320 that has resource information filter means 321 and resource information delivery means 322, and a resource information storage unit 340.
The conventional resource information collection and delivery system with this configuration operates as follows. That is, a filter expression 310 sent from the resource use device 300 to the resource providing device 320 by the filter expression sending means 301 is an expression for selecting resource information whose attribute value exceeds or does not exceed a predetermined threshold value, from many pieces of resource information stored in the resource information storage unit 340. In response to the filter expression 310 from the filter expression sending means 301, the resource providing device 320 uses the resource information filter means 321 to extract only resource information, which satisfies the filter expression 310, from the resource information storage unit 340 and uses the resource information delivery means 322 to deliver the extracted resource information to the resource use device 300 as resource information 330. For example, when the filter expression 310 indicating “a host with the CPU speed of 750 MHz or higher and a free memory capacity of 256 MB or larger” is sent by the filter expression sending means 301, the resource information filter means 321 extracts information on all hosts satisfying the condition from the resource information storage unit 340 and sends the extracted information to the resource use device 300. The resource use device 300 determines a resource to be actually used from the delivered resource information and use that resource. For example, when the resource is a host, a job is submitted to the determined host.
On the other hand, the conventional technologies for information search include the following. One technology (for example, see Patent Document 1) is that, when there are a plurality of databases to be searched, data satisfying a predetermined condition is searched for from a particular database and, only if the number of searched-for data items is smaller than a predetermined number, other databases are searched. Another technology (for example, see Patent Document 2) is that the so-called ranking search is performed in a web search operation on the Internet or in an information search operation for outputting an ordered search result.
[Patent Document 1]
Japanese Patent Kokai Publication No. JP-P2000-235583A
[Patent Document 2]
Japanese Patent Kokai Publication No. JP-P2004-94813A
[Non-Patent Document 1]
K. Czajkowski et al. “Grid Information Services for Distributed Resource Sharing” [online], [searched on Jul. 21, 2004], Internet <http://www.globus.org/research/papers/MDS-HPDC.pdf>[Non-Patent Document 2]
“MDS 2.2 User's Guide”, (Chapter 2-Chapter 4), The Globus Project, [online] [searched on Jul. 21, 2004], Internet <http://www.globus.org/mds/mdsusersguide.pdf>
If the resource information storage unit 340 in the conventional resource information collection and delivery system shown in FIG. 24 contains many pieces of resource information satisfying the condition specified by the filter expression 310, all such resource information is delivered to the resource use device 300. Although only one resource providing device 320 is shown in FIG. 24, there are usually many resource providing devices. Because the resource use device 300 collects resource information from each of those resource providing devices 320, the number of collected resource information pieces is further increased. Therefore, when the resource use device 300 has a separately defined evaluation expression for selecting more valuable resources from those resources satisfying the condition, specified by the filter expression 310, to select a resource to be actually used, the problem is that the amount of calculation on the resource use device 300 increases in proportion to the number of delivered resource information pieces. This requires the resource use device 300 to have sufficient calculation power.
A more rigid condition, if specified for the filter expression 310, could control the number of collected resource information pieces. However, the problem is that, because the resource use device 300 side usually has no way to identify the attribute distribution of the resource information stored in the resource information storage unit 340 of the resource providing devices 320, specifying a rigid condition requires many attempts on a trial and error basis with the result that the efficiency of resource information collection is decreased.
When the technology described in Patent Document 1 is used, resource information satisfying the condition of the filter expression 310 is collected first from a particular resource providing device 320 and, only if the number of resource information pieces is smaller than a predetermined number, resource information is collected also from other resource providing devices 320. The problem with this method is that more valuable resource information is sometimes not collected.
A ranking search is used in an Internet web search or a document search, as described in Patent Document 2, to output an ordered search result (with ranking). For example, points (scores) are calculated for the documents based on an evaluation criterion such as the number of keywords included in the documents when a keyword search is performed, or on an evaluation criterion such as the resemblance of a sentence to a specified sentence when a natural sentence search is performed, and the resulting documents are output in order of the points (scores). However, such evaluation criteria, which are set by the information providing side for ranking search, do not guarantee that highly ranked search results are always valuable to the user side. In addition, because each information providing device side ranks the result based on its own evaluation criterion, comparison among the ranks produced by a plurality of information providing devices is meaningless. Therefore, the problem with this method is that relative merits among search results cannot be determined.